class_docstr: Extract X-vector from speechbrain pretrained models
class_docstr_tok: ["Extract","X-vector","from","speechbrain","pretrained","models"]
code: def __call__(self, wav, in_sr):
      wav = self.audio_norm(torch.from_numpy(wav), in_sr).to(
          self.device
      )
      embeds = self.model.encode_batch(wav).detach().cpu().numpy()[0]
      return embeds
  
file_path: espnet/egs2/fsc_challenge/asr1/pyscripts/utils/evaluate_secs.py
imports: import argparse
  import fnmatch
  import logging
  import os
  from typing import List
  import librosa
  import numpy
  import soundfile
  import torch
  from scipy import spatial
  from speechbrain.dataio.preprocess import AudioNormalizer
  from speechbrain.pretrained import EncoderClassifier
label_desc: Use image node_id 2 for calling the XVExtractor obj's underlying member method code with example usage: obj.__call__(wav, in_sr) and returns: embeds